RESUMEN
Human platelets play a key role in hemostasis and thrombosis and have recently emerged as key regulators of inflammation. Platelets stored for transfusion produce pro-thrombotic and pro-inflammatory mediators implicated in adverse transfusion reactions. Correspondingly, these mediators are central players in pathological conditions including cardiovascular disease, the major cause of death in diabetics. In view of this, a mass spectrometry based proteomics study was performed on platelets collected from healthy and type-2 diabetics stored for transfusion. Strikingly, our innovative and sensitive proteomic approach identified 122 proteins that were either up- or down-regulated in type-2 diabetics relative to nondiabetic controls and 117 proteins whose abundances changed during a 5-day storage period. Notably, our studies are the first to characterize the proteome of platelets from diabetics before and after storage for transfusion. These identified differences allow us to formulate new hypotheses and experimentation to improve clinical outcomes by targeting "high risk platelets" that render platelet transfusion less effective or even unsafe.
Asunto(s)
Plaquetas/metabolismo , Conservación de la Sangre/métodos , Diabetes Mellitus Tipo 2/sangre , Proteoma/análisis , Proteómica/métodos , Adulto , Anciano , Bancos de Sangre , Cromatografía Líquida de Alta Presión , Femenino , Humanos , Integrina alfa2beta1/sangre , Masculino , Espectrometría de Masas , Persona de Mediana Edad , Transfusión de Plaquetas , Proteoma/clasificación , Factores de Tiempo , Adulto JovenRESUMEN
Assessment of differential protein abundance from the observed properties of detected peptides is an essential part of protein profiling based on shotgun proteomics. However, the abundance observed for shared peptides may be due to contributions from multiple proteins that are affected differently by a given treatment. Excluding shared peptides eliminates this ambiguity but may significantly decrease the number of proteins for which abundance estimates can be obtained. Peptide sharing within a family of biologically related proteins does not cause ambiguity if family members have a common response to treatment. On the basis of this concept, we have developed an approach for including shared peptides in the analysis of differential protein abundance in protein profiling. Data from a recent proteomics study of lung tissue from mice exposed to lipopolysaccharide, cigarette smoke, and a combination of these agents are used to illustrate our method. Starting from data where about half of the implicated database protein involved shared peptides, 82% of the affected proteins were grouped into families, based on FASTA annotation, with closure on peptide sharing. In many cases, a common abundance relative to control was sufficient to explain ion-current peak areas for peptides, both unique and shared, that identified biologically related proteins in a peptide-sharing closure group. On the basis of these results, we propose that peptide-sharing closure groups provide a way to include abundance data for shared peptides in quantitative protein profiling by high-throughput mass spectrometry.